scholarly journals Optimal estimation of snow and ice surface parameters from imaging spectroscopy measurements

2021 ◽  
Author(s):  
Niklas Bohn ◽  
Thomas Painter ◽  
David Thompson ◽  
Nimrod Carmon ◽  
Jouni Susiluoto ◽  
...  
Keyword(s):  
Imaging Spectroscopy ◽  
Optimal Estimation ◽  
Surface Parameters ◽  
Ice Surface ◽  
Snow And Ice

Optimal estimation of snow and ice surface parameters from imaging spectroscopy measurements

2021 ◽  
Vol 264 ◽  
pp. 112613
Author(s):  
Niklas Bohn ◽  
Thomas H. Painter ◽  
David R. Thompson ◽  
Nimrod Carmon ◽  
Jouni Susiluoto ◽  
...  
Keyword(s):  
Imaging Spectroscopy ◽  
Optimal Estimation ◽  
Surface Parameters ◽  
Ice Surface ◽  
Snow And Ice

Optimal estimation of snow and ice surface parameters from imaging spectroscopy measurements

2021 ◽  
Author(s):  
Niklas Bohn ◽  
David Thompson ◽  
Nimrod Carmon ◽  
Jouni Susiluoto ◽  
Michael Turmon ◽  
...  
Keyword(s):  
Liquid Water ◽  
Imaging Spectroscopy ◽  
Greenland Ice Sheet ◽  
Optimal Estimation ◽  
Surface Reflectance ◽  
Mixing Ratio ◽  
Surface Parameters ◽  
Ice Surface ◽  
Orbital Imaging ◽  
Snow And Ice

<p>Snow and ice melt processes are key variables in Earth energy-balance and hydrological modeling. Their quantification facilitates predictions of meltwater runoff and distribution and availability of fresh water. Furthermore, they are indicators of climate change and control the balance of the Earth's ice sheets. These processes decrease the surface reflectance with unique spectral patterns due to the accumulation of liquid water and light absorbing particles (LAP), making imaging spectroscopy a powerful tool to measure and map this phenomenon. Here we present a new method to retrieve snow grain size, liquid water fraction, and LAP mass mixing ratio from airborne and space borne imaging spectroscopy acquisitions. This methodology is based on a simultaneous retrieval of atmospheric and surface parameters using optimal estimation (OE), a retrieval technique which leverages prior knowledge and measurement noise in the inversion and also produces uncertainty estimates. We exploit statistical relationships between surface reflectance spectra and snow and ice properties to estimate their most probable quantities given the reflectance. To test this new algorithm we conducted a sensitivity analysis based on simulated top-of-atmosphere radiance spectra using the upcoming EnMAP orbital imaging spectroscopy mission, demonstrating an accurate estimation performance of snow and ice surface properties. An additional validation experiment using in-situ measurements of glacier algae mass mixing ratio and surface reflectance from the Greenland Ice Sheet yields promising results. Finally, we evaluated the retrieval capacity for all snow and ice properties with an AVIRIS-NG acquisition from the Greenland Ice Sheet demonstrating this approach’s potential and suitability for upcoming orbital imaging spectroscopy missions.</p>

scholarly journals Optimal Estimation of Snow and Ice Surface Parameters from Imaging Spectroscopy Measurements

2021 ◽  
Author(s):  
Urs Niklas Bohn ◽  
David Thompson ◽  
Nimrod Carmon ◽  
Jouni Susiluoto ◽  
Michael Turmon ◽  
...  
Keyword(s):  
Imaging Spectroscopy ◽  
Optimal Estimation ◽  
Surface Parameters ◽  
Ice Surface ◽  
Snow And Ice

scholarly journals Snow and ice applications of AVHRR in polar regions: report of a workshop held in Boulder, Colorado, 20 May 1992

1993 ◽  
Vol 17 ◽  
pp. 1-16 ◽  
Author(s):  
K. Steffen ◽  
R. Bindschadler ◽  
G. Casassa ◽  
J. Comiso ◽  
D. Eppler ◽  
...  
Keyword(s):  
Sea Ice ◽  
Satellite Data ◽  
Quality Data ◽  
Polar Regions ◽  
Data Set ◽  
Ice Surface ◽  
The Status ◽  
Ice Surface Temperature ◽  
Snow And Ice

The third symposium on Remote Sensing of Snow and Ice, organized by the International Glaciological Society, took place in Boulder, Colorado, 17–22 May 1992. As part of this meeting a total of 21 papers was presented on snow and ice applications of Advanced Very High Resolution Radiometer (AVHRR) satellite data in polar regions. Also during this meeting a NASA sponsored Workshop was held to review the status of polar surface measurements from AVHRR. In the following we have summarized the ideas and recommendations from the workshop, and the conclusions of relevant papers given during the regular symposium sessions. The seven topics discussed include cloud masking, ice surface temperature, narrow-band albedo, ice concentration, lead statistics, sea-ice motion and ice-sheet studies with specifics on applications, algorithms and accuracy, following recommendations for future improvements. In general, we can affirm the strong potential of AVHRR for studying sea ice and snow covered surfaces, and we highly recommend this satellite data set for long-term monitoring of polar process studies. However, progress is needed to reduce the uncertainty of the retrieved parameters for all of the above mentioned topics to make this data set useful for direct climate applications such as heat balance studies and others. Further, the acquisition and processing of polar AVHRR data must become better coordinated between receiving stations, data centers and funding agencies to guarantee a long-term commitment to the collection and distribution of high quality data.

scholarly journals Snow and ice applications of AVHRR in polar regions: report of a workshop held in Boulder, Colorado, 20 May 1992

1993 ◽  
Vol 17 ◽  
pp. 1-16 ◽  
Author(s):  
K. Steffen ◽  
R. Bindschadler ◽  
G. Casassa ◽  
J. Comiso ◽  
D. Eppler ◽  
...  
Keyword(s):  
Sea Ice ◽  
Satellite Data ◽  
Quality Data ◽  
Polar Regions ◽  
Data Set ◽  
Ice Surface ◽  
The Status ◽  
Ice Surface Temperature ◽  
Snow And Ice

The third symposium on Remote Sensing of Snow and Ice, organized by the International Glaciological Society, took place in Boulder, Colorado, 17–22 May 1992. As part of this meeting a total of 21 papers was presented on snow and ice applications of Advanced Very High Resolution Radiometer (AVHRR) satellite data in polar regions. Also during this meeting a NASA sponsored Workshop was held to review the status of polar surface measurements from AVHRR. In the following we have summarized the ideas and recommendations from the workshop, and the conclusions of relevant papers given during the regular symposium sessions. The seven topics discussed include cloud masking, ice surface temperature, narrow-band albedo, ice concentration, lead statistics, sea-ice motion and ice-sheet studies with specifics on applications, algorithms and accuracy, following recommendations for future improvements. In general, we can affirm the strong potential of AVHRR for studying sea ice and snow covered surfaces, and we highly recommend this satellite data set for long-term monitoring of polar process studies. However, progress is needed to reduce the uncertainty of the retrieved parameters for all of the above mentioned topics to make this data set useful for direct climate applications such as heat balance studies and others. Further, the acquisition and processing of polar AVHRR data must become better coordinated between receiving stations, data centers and funding agencies to guarantee a long-term commitment to the collection and distribution of high quality data.

scholarly journals Deriving Arctic 2 m air temperatures over snow and ice from satellite surface temperature measurements

2019 ◽  
Author(s):  
Pia Nielsen-Englyst ◽  
Jacob L. Høyer ◽  
Kristine S. Madsen ◽  
Rasmus T. Tonboe ◽  
Gorm Dybkjær
Keyword(s):  
Surface Temperature ◽  
Arctic Region ◽  
Satellite Observations ◽  
The Arctic ◽  
Ice Surface ◽  
Air Temperatures ◽  
In Situ Observations ◽  
The Arctic Region ◽  
Snow And Ice

Abstract. The Arctic region is responding heavily to climate change, and yet, the air temperature of Arctic, ice covered areas is heavily under-sampled when it comes to in situ measurements, and large uncertainties exist in weather- and reanalysis products. This paper presents a method for estimating daily mean 2 meter air temperatures (T2m) in the Arctic from satellite observations of skin temperature, using the Arctic and Antarctic ice Surface Temperatures from thermal Infrared (AASTI) satellite dataset, providing spatially detailed observations of the Arctic. The method is based on a linear regression model which has been developed using in situ observations and daily mean satellite ice surface skin temperatures combined with a seasonal variation to estimate daily T2m. The satellite derived T2m product including estimated uncertainties covers clear sky snow and ice surfaces in the Arctic region during the period 2000–2009. Comparison with independent in situ measured T2m gives average correlations of 95.5 % and 96.5 % and average root mean square errors of 3.47 °C and 3.19 °C for land ice and sea ice, respectively. The reconstruction provides a much better spatial coverage than the sparse in situ observations of T2m in the Arctic, is independent of numerical weather prediction model input and it therefore provides an important alternative to simulated air temperatures to be used for assimilation or global surface temperature reconstructions. A comparison between in situ T2m versus T2m from satellite and ERA-Interim shows that the T2m derived from satellite observations validate similar or better than ERA-Interim estimates in the Arctic.

Emerging investigator series: spatial distribution of dissolved organic matter in ice and at air–ice interfaces

2019 ◽  
Vol 21 (7) ◽  
pp. 1076-1084 ◽  
Author(s):  
Subha Chakraborty ◽  
Tara F. Kahan
Keyword(s):  
Organic Matter ◽  
Spatial Distribution ◽  
Dissolved Organic Matter ◽  
Surface Interactions ◽  
Heterogeneous Reactions ◽  
Organic Solutes ◽  
Ice Surface ◽  
Snow And Ice

Organic solutes in snow and ice can be distributed heterogeneously throughout the ice bulk and across the ice surface. This may affect air-surface interactions and heterogeneous reactions in snow-covered regions.

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